Target Tracking in Wireless Visual Sensor Networks: Challenges, Steps, and Metrics of Evaluation

In recent years, wireless sensor networks have been used in a wide range of applications such as smart cities, military, and environmental monitoring. Target tracking is one of the most interesting applications in this area of research, which mainly consists of detecting the targets that move in the area of interest and monitoring their motions. However, tracking a target using visual sensors is different and more difficult than that of scalar sensors due to the special characteristics of visual sensors, such as their directional limited field of view, and the nature and amount of the sensed data. In this paper, we first present the challenges of detection and target tracking in wireless visual sensor networks, then we propose a scheme that describes the basic steps of target tracking in these networks, we focus then on the tracking across camera nodes by presenting some metrics that can be considered when designing and evaluating this type of tracking approaches.

An Improved Image Steganography Scheme Based on Partial Preservation Embedding Algorithm for Wireless Visual Sensor Networks

With the continuous improvement of encryption algorithms, some applications based on the architecture of wireless visual sensor networks have gradually shifted their attention to the imperceptibility and antijamming performance of secret images. To reduce the probability of secret images being detected, the current research focuses on hiding secret data in the least-significant bit of the cover image in the spatial domain or embedding data into the coefficients of the high-frequency band in the transformational domain, which usually leads to poor performance in a hostile environment. Therefore, some researchers proposed to substitute the coefficients of the medium-frequency band in the transformational domain with secret information to enhance the anti-interference performance. However, this idea would severely affect the imperceptibility of secret images. As a result, an improved version based on the partial preservation embedding algorithm was designed in this paper. Theory analysis and simulation results indicate that the proposed scheme performs better than the existing methods by directly substituting the coefficients of the medium-frequency band in the transformational domain, especially in the case of strong noise interference.

A New System for Real-time Video Surveillance in Smart Cities Based on Wireless Visual Sensor Networks and Fog Computing

Nowadays, public security is becoming an increasingly serious issue in our society and its requirements have been extended from urban centers to all remote areas. Therefore, surveillance and security cameras are being deployed worldwide. Wireless Visual Sensor Networks nodes can be employed as camera nodes to monitor in the city without the need for any cables installation. However, these cameras are constrained in processing, memory, and energy resources. Also, they generate a massive amount of data that must be analyzed in real-time to ensure public safety and deal with emergency situations. As a result, data processing, information fusion, and decision making have to be executed on-site (near to the data collection location). Besides, surveillance cameras are directional sensors, which makes the coverage problem another issue to deal with. Therefore, we present a new system for real-time video surveillance in a smart city, in which transportations equipped with camera nodes are used as the mobile part of the system and an architecture based on fog computing and wireless visual sensor networks is adopted. Furthermore, we propose an approach for selecting the camera nodes that will participate in the tracking process and we simulated three different use cases to test the effectiveness of our system in terms of target detection. The simulation results show that our system is a promising solution for smart city surveillance applications.

Security Framework for Smart Visual Sensor Networks

Due to the significance of image data over the scalar data, the camera-integrated wireless sensor networks have attained the focus of researchers in the field of smart visual sensor networks. These networks are inexpensive and found wide application in surveillance and monitoring systems. The challenge is that these systems are resource deprived systems. The visual sensor node is typically an embedded system made up of a light weight processor, low memory, low bandwidth transceiver, and low-cost image sensor unit. As these networks carry sensitive information of the surveillance region, security and privacy protection are critical needs of the VSN. Due to resource limited nature of the VSN, the image encryption is crooked into an optimally lower issue, and many findings of image security in VSN are based on selective or partial encryption systems. The secure transmission of images is more trivial. Thus, in this chapter, a security frame work of smart visual sensor network built using energy-efficient image encryption and coding systems designed for VSN is presented.

Security Framework for Smart Visual Sensor Networks

Due to the significance of image data over the scalar data, the camera-integrated wireless sensor networks have attained the focus of researchers in the field of smart visual sensor networks. These networks are inexpensive and found wide application in surveillance and monitoring systems. The challenge is that these systems are resource deprived systems. The visual sensor node is typically an embedded system made up of a light weight processor, low memory, low bandwidth transceiver, and low-cost image sensor unit. As these networks carry sensitive information of the surveillance region, security and privacy protection are critical needs of the VSN. Due to resource limited nature of the VSN, the image encryption is crooked into an optimally lower issue, and many findings of image security in VSN are based on selective or partial encryption systems. The secure transmission of images is more trivial. Thus, in this chapter, a security frame work of smart visual sensor network built using energy-efficient image encryption and coding systems designed for VSN is presented.